RESUMO
Testing of pesticide leaching models against comprehensive field-scale measurements is necessary to increase confidence in their predictive ability when used as regulatory tools. Version 5.1 of the MACRO model was tested against measurements of water flow and the behaviour of bromide, bentazone [3-isopropyl-1H-2,1,3-benzothiadiazin-4(3H)-one-2,2-dioxide] and imidacloprid [1-(6-chloro-3-pyridylmethyl)-N-nitroimidazolidin-2-ylideneamine] in a cracked clay soil. In keeping with EU (FOCUS) procedures, the model was first calibrated against the measured moisture profiles and bromide concentrations in soil and in drain water. Uncalibrated pesticide simulations based on laboratory measurements of sorption and degradation were then compared with field data on the leaching of bentazone and imidacloprid. Calibrated parameter values indicated that a high degree of physical non-equilibrium (i.e. strong macropore flow) was necessary to describe solute transport in this soil. Comparison of measured and simulated bentazone concentration profiles revealed that the bulk of the bentazone movement in this soil was underestimated by MACRO. Nevertheless, the model simulated the dynamics of the bentazone breakthrough in drain water rather well and, in particular, accurately simulated the timing and the concentration level of the early bentazone breakthrough in drain water. The imidacloprid concentration profiles and its persistence in soil were simulated well. Moreover, the timing of the early imidacloprid breakthrough in the drain water was simulated well, although the simulated concentrations were about 2-3 times larger than measured. Deep groundwater concentrations for all substances were underestimated by MACRO, although it simulated concentrations in the shallow groundwater reasonably well. It is concluded that, in the context of ecotoxicological risk assessments for surface water, MACRO can give reasonably good simulations of pesticide concentrations in water draining from cracking clay soils, but that prior calibration against hydrologic and tracer data is desirable to reduce uncertainty and improve accuracy.